Graduate students and early-career scientists from Russia and Germany have spent the past week congregating...

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Graduate students and early-career scientists from Russia and Germany have spent the past week congregating in the halls of Skoltech to share their latest research and develop valuable connections with their international counterparts.

Thursday marked the end of the seventh annual German-Russian Week of the Young Researcher (WYR) – an event that aims to foster ties between the scientific communities of these two nations.

“The main goal of [WYR] is to bring together young scientists and senior scientists from Russia and Germany and to give them an overview about current scientific topics, and hopefully to build new working groups and partnerships in this field,” said Mikhail Rusakov, coordinator of the German Houses for Research and Innovation (DWIH Moscow), the event’s key organizer.

Other organizers included the German Research Foundation (DFG), Germany’s main academic grant funding organization, and the German Academic Exchange Service (DAAD), an organization that supports study abroad programs, both of which operate in Moscow under the DWIH umbrella. The German Embassy in Moscow also provided support.

Past WYR events have been held in institutions in other regions across Russia, including Kazan, Novosibirsk and St. Petersburg. Rusakov explained that Skoltech was chosen to host this year’s event because: “It is a modern and innovative institute, where the topics of this year – Biomedicine and Computational Biology – are studied. The provost of Skoltech – Professor Rupert Gerzer – is also a German professor.”

Each year the event focuses on a different scientific field. This year, it centered on Computational Biology and Biomedicine.

Lecture topics ran the gamut from mutational changes during the development of cancer, to detecting the genetic causes of inherited rare diseases, to the convergence of biomedicine and engineering.

DWIH Director Peter Hiller noted that Gerzer’s deep roots in German academia proved key to the success of this year’s conference. Being tapped into a network of professors at some of Germany’s leading universities, Gerzer was able to help attract top-flight academics and their research teams.

Hiller added that by hosting the conference, Skoltech was able to expand its repertoire of international partner universities: “Many of the German scientists attending the event came to Russia for the first time this week, providing Skoltech with an excellent opportunity to lay the foundations for a collaboration with German universities.”

Skoltech Provost Gerzer views strengthening ties with Germany as one of his important tasks at the institute: “I am still deeply connected with the German research community and always enjoy seeing how enthusiastic my German colleagues get about collaborating with Russian institutions once they have arrived here and have seen all the great developments.”

German attendees included scholars from the Technical University of Munich (TUM), the Ludwig-Maximilian University of Munich, the University of Stuttgart, the University of Rostock and the Free University of Berlin.

This year’s event featured two novel components: poster sessions and an innovation section.

The former gave select young researchers from Germany and Russia the opportunity to deliver visual presentations on their current research interests.

The latter brought in industry representatives, including German companies Biomax Informatics AG and Bayer, and Russian company Biosoft – a Skolkovo resident – to Skoltech to provide young scientists with practical business innovation tips, including lessons on how to transform a research project into a successful company.

DFG Vice President Frank Allgöwer, who attended the 2016 WYR conference as well, said he was highly impressed with the range of topics covered during this year’s event, as well as with the quality of the research presented by young scientists from both countries. He went on to commend the “constructive spirit that carried through each day of the conference.”

Going forward, the WYR organizers plan to continue the poster and innovation sessions. “I think these sessions were very successful and very interesting, and we plan to repeat them in the coming years,” Hiller said.

The week was also replete with networking opportunities – from coffee breaks and shared mealtimes to cocktail receptions and an evening boat ride through Moscow. Fun though they may have been, these activities were guided by a purpose. The WYR organizers believe it is imperative to foster meaningful connections between conference attendees.

“In our opinion it’s very important to nurture lasting contact between scientists – especially among the younger generation – so they can communicate with each other, exchange experiences and discuss their projects, and not only make presentations,” Rusakov said.

Relying on nanotechnology, scientists from Russia and Germany led by Skoltech research scientist Fedor Fedorov...

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Relying on nanotechnology, scientists from Russia and Germany led by Skoltech research scientist Fedor Fedorov have developed an innovative solution for detecting traces of gas in the air.

Given our growing global population and the current level of industrial output, humanity is in urgent need of accurate and affordable gas sensors that can reliably monitor the state of the atmosphere. The ideal gas sensor would be highly sensitive and selective, enabling it to detect even the lightest traces of certain types of substances in the air. It would also be inexpensive to produce and energy-efficient.

At present, most gas sensors are made of various materials: transition metal oxides, carbon materials (graphene, carbon nanotubes) and various polymers. Despite the obvious progress in increasing the sensitivity of such sensors, inadequate selectivity remains a key problem. Furthermore, there is always a need for new technologies that are compatible with modern electronics.

Scientists from several universities in Russia (Skoltech, the Yuri Gagarin State Technical University of Saratov and the Russian Academy of Sciences’ Institute of Radioengineering and Electronics) and Germany (Karlsruhe Institute of Technology) teamed up to address these challenges.

As a result of their research, they have developed a nanotechnological solution for creating a highly sensitive and selective sensor. These new sensors will consist of arrays of nanotubes made of titanium dioxide.

Array titanium dioxide nanotubes (electron tomography).

They chose titanium dioxide because it exhibits good chemoresistive properties; its resistance level varies with the appearance of gas vapors in the atmosphere.

The device is able to identify which type of substance it’s detecting by dividing a given material into segments to be a set of sensors and processing the obtained vector signal using pattern recognition techniques. This enables it to create a fingerprint of sorts for each type of gas it detects.

In addition to its environmental impact, this device could prove effective in helping doctors diagnose ailments in their patients. When people have certain diseases, like diabetes and various cancers, their breath contain abnormally high amounts of certain organic gases, particularly acetone. The gas sensor would be able to detect these abnormalities in patients.

The developed technology is inexpensive and scalable to be easily implemented in modern electronics. It utilized soft chemistry methods to fabricate the nanotubular array which is then transferred onto the chip to serve as sensitive layer.

“During our laboratory studies, we were able to test the response of our system to acetone, isopropanol and ethanol. The latter two gases are very similar to each other. And not only were we able to detect these gases; we were able to distinguish them from one another. To do this, we trained our system to identify the appearance of a gas by its ‘fingerprint’,” said Fedorov.

Electronic tomography of several nanotubes of titanium dioxide

The results of the study have been published in the prestigious research journal Scientific Reports.

Rise of the quantum thinking machines Quantum computers can be made to utilize effects such...

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Rise of the quantum thinking machines

Quantum computers can be made to utilize effects such as quantum coherence and entanglement to accelerate machine learning.

Although we typically view information as being an abstract or virtual entity, information of course must be stored in a physical medium. Information processing devices, such as computers and your iphone, are therefore fundamentally governed by the laws of physics. In this way, the fundamental physical limits of an agent’s ability to learn are governed by the laws of physics. As the best known theory of physics is quantum theory, quantum theory therefore ultimately must be used to determine the absolute physical limits of a machine’s ability to learn.

A quantum algorithm is a stepwise procedure performed on a quantum computer to solve a problem, such as searching a database. Quantum machine learning software makes use of quantum algorithms to process information in ways that classical computers cannot. These quantum effects open up exciting new avenues which can, in principle, outperform the best known classical algorithms when solving certain machine learning problems. This is known as quantum enhanced machine learning.

Machine learning methods use mathematical algorithms to search for certain patterns in large data sets. Machine learning is widely used in biotechnology, pharmaceuticals, particle physics and many other fields. Thanks to the ability to adapt to new data, machine learning greatly exceeds the ability of people. Despite this, machine learning cannot cope with certain difficult tasks.

Quantum enhancement is predicted to be possible for a host of machine learning tasks, ranging from optimization to quantum enhanced deep learning.

In the new paper published in Nature, a group of scientists led by Skoltech Associate Professor Jacob Biamonte produced a feasibility analysis which outlined what steps can be taken for quantum enhanced machine learning to be born out in practice.

The prospects of using quantum computers to accelerate machine learning has generated recent excitement due to the increasing capabilities of quantum computers. This includes a commercially available 2000 spin quantum accelerated annealing by the Canada-based company D-Wave Systems Inc. and a 16 qubit universal quantum processor by IBM which is accessible via a (currently free) cloud service.

The availability of these devices has led to increased interest from the machine learning community. The interest comes as a bit of a shock to the traditional quantum physics community, in which researchers have thought that the primary applications of quantum computers would be using quantum computers to simulate chemical physics, which can be used in the pharmaceutical industry for drug discovery. However, certain quantum systems can be mapped to certain machine learning models, particularly deep learning models. Quantum machine learning can be used to work in tandem with these existing methods for quantum chemical emulation, leading to even greater capabilities for a new era of quantum technology.

“Early on the team burned the midnight oil over Skype debating what the field even was — our synthesis will hopefully solidify topical importance. We submitted our draft to Nature, going forward subject to significant changes: all-in-all we ended up writing three versions over eight months with nothing more than the title in common,” said lead study author Biamonte.

Inspector Cloud, an automated auditing startup powered by some of Skoltech’s great computer vision minds,...

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Inspector Cloud, an automated auditing startup powered by some of Skoltech’s great computer vision minds, has won a coveted spot in a New York accelerator – an honor that comes accompanied by a grant of upwards of $130,000.

This victory didn’t come easy; Inspector Cloud was up against 600 competitors from 30 different countries, vying for 13 spots in this year’s Starta Accelorator program, which aims to build bridges for Russian and Eastern European companies wishing to launch their businesses stateside.

Inspector Cloud was developed to relieve many of the labor and resource burdens traditionally associated with monitoring a store’s inventory.

“We came up with the idea about a year ago that retail needs a solution to monitoring the presence of goods on shelves,” said Alexander Berenov, Inspector Cloud’s Chief Executive Officer (CEO).

“We had many talks with prospective partners and clients and determined that actually they needed this technology and were searching for a Russian vendor. We then decided to focus intensely on developing a solution,” he said.

Inventory monitoring is necessary for reasons ranging from annual accounting requirements to meeting customer demand and responding to a lack of customer interest in certain products.

Traditionally, the process has required employees to manually count items on a store’s shelves and in its storage facilities, and subsequently to compare these figures with those in the company’s accounting records.

Many businesses require an ongoing general monitoring of supplies, as well as a comprehensive inventory counting process at least once a year. As these comprehensive counts typically have to take place after hours, the result is long hours for employees and costly overtime pay for management.

Inspector Cloud decimates the time and energy involved in the traditional process by creating an automated alternative to the manual process. Specifically, using the startup’s software, shop employees can photograph goods on a store’s shelf, and then enter these photos into a system that relies on neural networks to categorize and count the goods.

According to the company’s website, its algorithm is able to properly identify 96% of products based on photos; the 4% that can’t initially be identified are then used to train the neural network in order to prevent subsequent mistakes.

Based on these results, Inspector Cloud is able to provide retailers with real time audits, and to notify store management within three minutes of detecting abnormalities.

In addition to revolutionizing the auditing process, the company claims that its services can boost sales by giving retailers keen insights into which products tend to fly off the shelves, which ones tend to gather dust and what correlating factors may have a bearing on either scenario.

Inspector Cloud also works with fast-moving consumer goods (FMCG) companies like beauty empire L’Oréal and chewing gum giant Wrigley, which have an interest in monitoring the share of shelf space their products occupy in stores as compared with their competitors, as well as the movement of their goods in certain stores.

“We offer retailers a free license to use our services, and in exchange we take the data we retrieve from the stores’ usage of our service and then sell it to the FMCG brands. This is a novel business model in this market, and it’s one of our main distinguishing points,” Berenov said.

Boyko explained that his role encompasses a vast range of responsibilities: “As CTO, I am responsible for product and technology development. As always with startups, this covers a broad area, ranging from listening to clients’ needs to implementing advanced deep learning algorithms to troubleshooting service continuity on weekends, just to name a few of my duties. I also manage a small but very talented R&D team. With time, my responsibilities have drifted from inventing technology demonstrators to satisfying clients on a daily basis with a bulletproof product.”

Boyko explained that his initial motivation to get involved with Inspector Cloud arose from his excitement over the potential convergence of offline retail with the latest breakthroughs in computer vision.

His early enthusiasm has borne fruit. “One year later, I still believe Inspector Cloud has offered the best product-market fit of any project I’ve taken on so far,” he said.

Lempitsky was drawn to the project based on its drive and promise: “I was attracted by the motivated and talented team, which I believed had a very good chance for success.”

He added that the team’s close affiliation with CDISE made the collaboration feel all the more natural.

Lempitsky’s goal in working on the project is to bolster the everyday use of computer vision technologies: “Automating retail inventory is a challenging use case for computer vision and some of the technology I have been working on in recent years with my students and collaborators. This technology includes recognition systems based on deep neural networks and large-scale visual search. Helping to implement such technology for a real-life task is obviously exciting.”

Now that Investor Cloud has secured a spot with the Starta Accelorator, Berenov is off to New York to participate in a 3.5-month intensive program aimed at arming his team with the strategies and funds they’ll need to penetrate the US market.